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Participation in wiki communities: reconsidering their statistical characterization
Peer production online communities are groups of people that collaboratively engage in the building of common resources such as wikis and open source projects. In such communities, participation is highly unequal: few people concentrate the majority of the workload, while the rest provide irregular...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8771763/ https://www.ncbi.nlm.nih.gov/pubmed/35111908 http://dx.doi.org/10.7717/peerj-cs.792 |
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author | Tenorio-Fornés, Ámbar Arroyo, Javier Hassan, Samer |
author_facet | Tenorio-Fornés, Ámbar Arroyo, Javier Hassan, Samer |
author_sort | Tenorio-Fornés, Ámbar |
collection | PubMed |
description | Peer production online communities are groups of people that collaboratively engage in the building of common resources such as wikis and open source projects. In such communities, participation is highly unequal: few people concentrate the majority of the workload, while the rest provide irregular and sporadic contributions. The distribution of participation is typically characterized as a power law distribution. However, recent statistical studies on empirical data have challenged the power law dominance in other domains. This work critically examines the assumption that the distribution of participation in wikis follows such distribution. We use statistical tools to analyse over 6,000 wikis from Wikia/Fandom, the largest wiki repository. We study the empirical distribution of each wiki comparing it with different well-known skewed distributions. The results show that the power law performs poorly, surpassed by three others with a more moderated heavy-tail behavior. In particular, the truncated power law is superior to all competing distributions, or superior to some and as good as the rest, in 99.3% of the cases. These findings have implications that can inform a better modeling of participation in peer production, and help to produce more accurate predictions of the tail behavior, which represents the activity and frequency of the core contributors. Thus, we propose to consider the truncated power law as the distribution to characterize participation distribution in wiki communities. Furthermore, the truncated power law parameters provide a meaningful interpretation to characterize the community in terms of the frequency of participation of occasional contributors and how unequal are the group of core contributors. Finally, we found a relationship between the parameters and the productivity of the community and its size. These results open research venues for the characterization of communities in wikis and in online peer production. |
format | Online Article Text |
id | pubmed-8771763 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87717632022-02-01 Participation in wiki communities: reconsidering their statistical characterization Tenorio-Fornés, Ámbar Arroyo, Javier Hassan, Samer PeerJ Comput Sci Human-Computer Interaction Peer production online communities are groups of people that collaboratively engage in the building of common resources such as wikis and open source projects. In such communities, participation is highly unequal: few people concentrate the majority of the workload, while the rest provide irregular and sporadic contributions. The distribution of participation is typically characterized as a power law distribution. However, recent statistical studies on empirical data have challenged the power law dominance in other domains. This work critically examines the assumption that the distribution of participation in wikis follows such distribution. We use statistical tools to analyse over 6,000 wikis from Wikia/Fandom, the largest wiki repository. We study the empirical distribution of each wiki comparing it with different well-known skewed distributions. The results show that the power law performs poorly, surpassed by three others with a more moderated heavy-tail behavior. In particular, the truncated power law is superior to all competing distributions, or superior to some and as good as the rest, in 99.3% of the cases. These findings have implications that can inform a better modeling of participation in peer production, and help to produce more accurate predictions of the tail behavior, which represents the activity and frequency of the core contributors. Thus, we propose to consider the truncated power law as the distribution to characterize participation distribution in wiki communities. Furthermore, the truncated power law parameters provide a meaningful interpretation to characterize the community in terms of the frequency of participation of occasional contributors and how unequal are the group of core contributors. Finally, we found a relationship between the parameters and the productivity of the community and its size. These results open research venues for the characterization of communities in wikis and in online peer production. PeerJ Inc. 2022-01-03 /pmc/articles/PMC8771763/ /pubmed/35111908 http://dx.doi.org/10.7717/peerj-cs.792 Text en ©2022 Tenorio-Fornés et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Human-Computer Interaction Tenorio-Fornés, Ámbar Arroyo, Javier Hassan, Samer Participation in wiki communities: reconsidering their statistical characterization |
title | Participation in wiki communities: reconsidering their statistical characterization |
title_full | Participation in wiki communities: reconsidering their statistical characterization |
title_fullStr | Participation in wiki communities: reconsidering their statistical characterization |
title_full_unstemmed | Participation in wiki communities: reconsidering their statistical characterization |
title_short | Participation in wiki communities: reconsidering their statistical characterization |
title_sort | participation in wiki communities: reconsidering their statistical characterization |
topic | Human-Computer Interaction |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8771763/ https://www.ncbi.nlm.nih.gov/pubmed/35111908 http://dx.doi.org/10.7717/peerj-cs.792 |
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